default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDRamesh Raskar
Person information
- affiliation: MIT, Cambridge, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j93]Seungeun Oh
, Hyelin Nam, Jihong Park, Praneeth Vepakomma, Ramesh Raskar, Mehdi Bennis, Seong-Lyun Kim:
Mix2SFL: Two-Way Mixup for Scalable, Accurate, and Communication-Efficient Split Federated Learning. IEEE Trans. Big Data 10(3): 238-248 (2024)- [c238]Ayush Chopra, Arnau Quera-Bofarull, Nurullah Giray Kuru, Michael J. Wooldridge, Ramesh Raskar:
Private Agent-Based Modeling. AAMAS 2024: 381-390 - [c237]Ayush Chopra, Jayakumar Subramanian, Balaji Krishnamurthy, Ramesh Raskar:
flame: A Framework for Learning in Agent-based ModEls. AAMAS 2024: 391-399 - [c236]Gauri Gupta, Ritvik Kapila, Ayush Chopra, Ramesh Raskar:
First 100 days of Pandemic: An Interplay of Pharmaceutical, Behavioral and Digital Interventions - A Study using Agent Based Modeling. AAMAS 2024: 761-770 - [c235]Zhaoxuan Wu, Mohammad Mohammadi Amiri, Ramesh Raskar, Bryan Kian Hsiang Low:
Incentive-Aware Federated Learning with Training-Time Model Rewards. ICLR 2024 - [i111]Gauri Gupta, Ritvik Kapila, Ayush Chopra, Ramesh Raskar:
First 100 days of pandemic; an interplay of pharmaceutical, behavioral and digital interventions - A study using agent based modeling. CoRR abs/2401.04795 (2024) - [i110]Abhishek Singh, Gauri Gupta, Ritvik Kapila, Yichuan Shi, Alex Dang, Sheshank Shankar, Mohammed Ehab, Ramesh Raskar:
CoDream: Exchanging dreams instead of models for federated aggregation with heterogeneous models. CoRR abs/2402.15968 (2024) - [i109]Zaid Tasneem, Akshat Dave, Abhishek Singh, Kushagra Tiwary, Praneeth Vepakomma, Ashok Veeraraghavan, Ramesh Raskar:
DecentNeRFs: Decentralized Neural Radiance Fields from Crowdsourced Images. CoRR abs/2403.13199 (2024) - [i108]Charles Lu, Baihe Huang, Sai Praneeth Karimireddy, Praneeth Vepakomma, Michael I. Jordan, Ramesh Raskar:
Data Acquisition via Experimental Design for Decentralized Data Markets. CoRR abs/2403.13893 (2024) - [i107]Manasi Muglikar, Siddharth Somasundaram, Akshat Dave, Edoardo Charbon, Ramesh Raskar, Davide Scaramuzza:
Event Cameras Meet SPADs for High-Speed, Low-Bandwidth Imaging. CoRR abs/2404.11511 (2024) - [i106]Ayush Chopra, Arnau Quera-Bofarull, Nurullah Giray Kuru, Michael J. Wooldridge, Ramesh Raskar:
Private Agent-Based Modeling. CoRR abs/2404.12983 (2024) - [i105]Yichuan Shi, Olivera Kotevska, Viktor Reshniak, Abhishek Singh, Ramesh Raskar:
Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy. CoRR abs/2405.10376 (2024) - [i104]Charles Lu, Mohammad Mohammadi Amiri, Ramesh Raskar:
Data Measurements for Decentralized Data Markets. CoRR abs/2406.04257 (2024) - [i103]Akshat Dave, Tianyi Zhang, Aaron Young, Ramesh Raskar, Wolfgang Heidrich, Ashok Veeraraghavan:
NeST: Neural Stress Tensor Tomography by leveraging 3D Photoelasticity. CoRR abs/2406.10212 (2024) - [i102]Seungeun Oh, Sihun Baek, Jihong Park, Hyelin Nam, Praneeth Vepakomma, Ramesh Raskar, Mehdi Bennis, Seong-Lyun Kim:
Privacy-Preserving Split Learning with Vision Transformers using Patch-Wise Random and Noisy CutMix. CoRR abs/2408.01040 (2024) - 2023
- [c234]Mohammad Mohammadi Amiri, Frederic Berdoz, Ramesh Raskar:
Fundamentals of Task-Agnostic Data Valuation. AAAI 2023: 9226-9234 - [c233]Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Arnau Quera-Bofarull, Balaji Krishnamurthy, B. Aditya Prakash, Ramesh Raskar:
Differentiable Agent-based Epidemiology. AAMAS 2023: 1848-1857 - [c232]Arnau Quera-Bofarull, Ayush Chopra, Joseph Aylett-Bullock, Carolina Cuesta-Lázaro, Anisoara Calinescu, Ramesh Raskar, Michael J. Wooldridge:
Don't Simulate Twice: One-Shot Sensitivity Analyses via Automatic Differentiation. AAMAS 2023: 1867-1876 - [c231]Siddharth Somasundaram, Akshat Dave, Connor Henley, Ashok Veeraraghavan, Ramesh Raskar:
Role of Transients in Two-Bounce Non-Line-of-Sight Imaging. CVPR 2023: 9192-9201 - [c230]Kushagra Tiwary, Akshat Dave, Nikhil Behari, Tzofi Klinghoffer, Ashok Veeraraghavan, Ramesh Raskar:
ORCa: Glossy Objects as Radiance-Field Cameras. CVPR 2023: 20773-20782 - [c229]Praneeth Vepakomma, Yulia Kempner, Rodmy Paredes Alfaro, Ramesh Raskar:
Parallel Quasi-Concave Set Function Optimization for Scalability Even Without Submodularity. HPEC 2023: 1-8 - [c228]Tzofi Klinghoffer, Jonah Philion, Wenzheng Chen, Or Litany, Zan Gojcic, Jungseock Joo, Ramesh Raskar, Sanja Fidler, José M. Álvarez:
Towards Viewpoint Robustness in Bird's Eye View Segmentation. ICCV 2023: 8481-8490 - [c227]Tzofi Klinghoffer, Kushagra Tiwary, Nikhil Behari, Bhavya Agrawalla, Ramesh Raskar:
DISeR: Designing Imaging Systems with Reinforcement Learning. ICCV 2023: 23575-23585 - [c226]Charles Lu, Yaodong Yu, Sai Praneeth Karimireddy, Michael I. Jordan, Ramesh Raskar:
Federated Conformal Predictors for Distributed Uncertainty Quantification. ICML 2023: 22942-22964 - [c225]Abhishek Singh, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar:
Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release. NeurIPS 2023 - [c224]Indrajit Ray, Bhavani Thuraisingham, Jaideep Vaidya, Sharad Mehrotra, Vijayalakshmi Atluri, Indrakshi Ray, Murat Kantarcioglu, Ramesh Raskar, Babak Salimi, Steve Simske, Nalini Venkatasubramanian, Vivek K. Singh:
SAFE-PASS: Stewardship, Advocacy, Fairness and Empowerment in Privacy, Accountability, Security, and Safety for Vulnerable Groups. SACMAT 2023: 145-155 - [c223]Seung-Hwan Baek, Ramesh Raskar, Jinwei Ye, Akshat Dave, Achuta Kadambi, Huaijin George Chen:
Polarization-Based Visual Computing. SIGGRAPH Courses 2023: 13:1 - [i101]Siddharth Somasundaram, Akshat Dave, Connor Henley, Ashok Veeraraghavan, Ramesh Raskar:
Role of Transients in Two-Bounce Non-Line-of-Sight Imaging. CoRR abs/2304.01308 (2023) - [i100]Gauri Gupta, Ritvik Kapila, Keshav Gupta, Ramesh Raskar:
Domain Generalization In Robust Invariant Representation. CoRR abs/2304.03431 (2023) - [i99]Charles Lu, Yaodong Yu, Sai Praneeth Karimireddy, Michael I. Jordan, Ramesh Raskar:
Federated Conformal Predictors for Distributed Uncertainty Quantification. CoRR abs/2305.17564 (2023) - [i98]Bhawesh Kumar, Charlie Lu, Gauri Gupta, Anil Palepu, David R. Bellamy, Ramesh Raskar, Andrew Beam:
Conformal Prediction with Large Language Models for Multi-Choice Question Answering. CoRR abs/2305.18404 (2023) - [i97]Tzofi Klinghoffer, Jonah Philion, Wenzheng Chen, Or Litany, Zan Gojcic, Jungseock Joo, Ramesh Raskar, Sanja Fidler, José M. Álvarez:
Towards Viewpoint Robustness in Bird's Eye View Segmentation. CoRR abs/2309.05192 (2023) - [i96]Tzofi Klinghoffer, Kushagra Tiwary, Nikhil Behari, Bhavya Agrawalla, Ramesh Raskar:
DISeR: Designing Imaging Systems with Reinforcement Learning. CoRR abs/2309.13851 (2023) - [i95]Tzofi Klinghoffer, Xiaoyu Xiang, Siddharth Somasundaram, Yuchen Fan, Christian Richardt, Ramesh Raskar, Rakesh Ranjan:
PlatoNeRF: 3D Reconstruction in Plato's Cave via Single-View Two-Bounce Lidar. CoRR abs/2312.14239 (2023) - [i94]Nikhil Behari, Akshat Dave, Kushagra Tiwary, William Yang, Ramesh Raskar:
SUNDIAL: 3D Satellite Understanding through Direct, Ambient, and Complex Lighting Decomposition. CoRR abs/2312.16215 (2023) - 2022
- [j92]Connor Henley, Joseph Hollmann, Ramesh Raskar:
Bounce-Flash Lidar. IEEE Trans. Computational Imaging 8: 411-424 (2022) - [c222]Praneeth Vepakomma, Julia Balla, Ramesh Raskar:
PrivateMail: Supervised Manifold Learning of Deep Features with Privacy for Image Retrieval. AAAI 2022: 8503-8511 - [c221]Gharib Gharibi, Babak Poorebrahim Gilkalaye, Praneeth Vepakomma, Zachi Attia, Riddhiman Das, Suraj Kapa, Ramesh Raskar:
Blind Inference: An Automated Privacy-Preserving Prediction Service using Secure Multi-Party Computation for Medical Applications. AMIA 2022 - [c220]Kushagra Tiwary, Tzofi Klinghoffer, Ramesh Raskar:
Towards Learning Neural Representations from Shadows. ECCV (33) 2022: 300-316 - [c219]Ayush Chopra, Abhinav Java, Abhishek Singh, Vivek Sharma, Ramesh Raskar:
Learning to Censor by Noisy Sampling. ECCV (13) 2022: 378-395 - [c218]Abhishek Singh, Ethan Garza, Ayush Chopra, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar:
Decouple-and-Sample: Protecting Sensitive Information in Task Agnostic Data Release. ECCV (13) 2022: 499-517 - [c217]Tzofi Klinghoffer, Siddharth Somasundaram, Kushagra Tiwary, Ramesh Raskar:
Physics vs. Learned Priors: Rethinking Camera and Algorithm Design for Task-Specific Imaging. ICCP 2022: 1-12 - [c216]Gharib Gharibi, Ravi Patel, Anissa Khan, Babak Poorebrahim Gilkalaye, Praneeth Vepakomma, Ramesh Raskar, Steve Penrod, Greg Storm, Riddhiman Das:
An Automated Framework for Distributed Deep Learning-A Tool Demo. ICDCS 2022: 1302-1305 - [c215]Seungeun Oh, Jihong Park, Praneeth Vepakomma, Sihun Baek, Ramesh Raskar, Mehdi Bennis, Seong-Lyun Kim:
LocFedMix-SL: Localize, Federate, and Mix for Improved Scalability, Convergence, and Latency in Split Learning. WWW 2022: 3347-3357 - [p1]Praneeth Vepakomma, Ramesh Raskar:
Split Learning: A Resource Efficient Model and Data Parallel Approach for Distributed Deep Learning. Federated Learning 2022: 439-451 - [i93]Ibrahim Suat Evren, Praneeth Vepakomma, Ramesh Raskar:
The Privacy-Welfare Trade-off: Effects of Differential Privacy on Influence & Welfare in Social Choice. CoRR abs/2201.10115 (2022) - [i92]Ayush Chopra, Abhinav Java, Abhishek Singh, Vivek Sharma, Ramesh Raskar:
Learning to Censor by Noisy Sampling. CoRR abs/2203.12192 (2022) - [i91]Abhishek Singh, Ethan Garza, Ayush Chopra, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar:
Decouple-and-Sample: Protecting sensitive information in task agnostic data release. CoRR abs/2203.13204 (2022) - [i90]Kushagra Tiwary, Tzofi Klinghoffer, Ramesh Raskar:
Towards Learning Neural Representations from Shadows. CoRR abs/2203.15946 (2022) - [i89]Tzofi Klinghoffer, Kushagra Tiwary, Arkadiusz Balata, Vivek Sharma, Ramesh Raskar:
Physically Disentangled Representations. CoRR abs/2204.05281 (2022) - [i88]Tzofi Klinghoffer, Siddharth Somasundaram, Kushagra Tiwary, Ramesh Raskar:
Physics vs. Learned Priors: Rethinking Camera and Algorithm Design for Task-Specific Imaging. CoRR abs/2204.09871 (2022) - [i87]Sihun Baek, Jihong Park, Praneeth Vepakomma, Ramesh Raskar, Mehdi Bennis, Seong-Lyun Kim:
Visual Transformer Meets CutMix for Improved Accuracy, Communication Efficiency, and Data Privacy in Split Learning. CoRR abs/2207.00234 (2022) - [i86]Praneeth Vepakomma, Mohammad Mohammadi Amiri, Clément L. Canonne, Ramesh Raskar, Alex Pentland:
Private independence testing across two parties. CoRR abs/2207.03652 (2022) - [i85]Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Balaji Krishnamurthy, B. Aditya Prakash, Ramesh Raskar:
Differentiable Agent-based Epidemiology. CoRR abs/2207.09714 (2022) - [i84]Chris Clifton, Bradley A. Malin, Anna Oganian, Ramesh Raskar, Vivek Sharma:
A Roadmap for Greater Public Use of Privacy-Sensitive Government Data: Workshop Report. CoRR abs/2208.01636 (2022) - [i83]Mohammad Mohammadi Amiri, Frederic Berdoz, Ramesh Raskar:
Fundamentals of Task-Agnostic Data Valuation. CoRR abs/2208.12354 (2022) - [i82]Connor Henley, Siddharth Somasundaram, Joseph Hollmann, Ramesh Raskar:
Detection and Mapping of Specular Surfaces Using Multibounce Lidar Returns. CoRR abs/2209.03336 (2022) - [i81]Seungeun Oh, Jihong Park, Sihun Baek, Hyelin Nam, Praneeth Vepakomma, Ramesh Raskar, Mehdi Bennis, Seong-Lyun Kim:
Differentially Private CutMix for Split Learning with Vision Transformer. CoRR abs/2210.15986 (2022) - [i80]Frédéric Berdoz, Abhishek Singh, Martin Jaggi, Ramesh Raskar:
Scalable Collaborative Learning via Representation Sharing. CoRR abs/2211.10943 (2022) - [i79]Kushagra Tiwary, Akshat Dave, Nikhil Behari, Tzofi Klinghoffer, Ashok Veeraraghavan, Ramesh Raskar:
ORCa: Glossy Objects as Radiance Field Cameras. CoRR abs/2212.04531 (2022) - 2021
- [j91]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14(1-2): 1-210 (2021) - [j90]Ayush Bhandari, Felix Krahmer, Ramesh Raskar:
On Unlimited Sampling and Reconstruction. IEEE Trans. Signal Process. 69: 3827-3839 (2021) - [c214]Abhishek Singh, Ayush Chopra, Ethan Garza, Emily Zhang, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar:
DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for Deep Neural Networks. CVPR 2021: 12125-12135 - [c213]Praneeth Vepakomma, Abhishek Singh, Emily Zhang, Otkrist Gupta, Ramesh Raskar:
NoPeek-Infer: Preventing face reconstruction attacks in distributed inference after on-premise training. FG 2021: 1-8 - [c212]Rohan Iyer, Regina Rex, Kevin P. McPherson, Darshan Gandhi, Aryan Mahindra, Abhishek Singh, Ramesh Raskar:
Spatial K-anonymity: A Privacy-preserving Method for COVID-19 Related Geo-spatial Technologies. GISTAM 2021: 75-81 - [c211]Yusuke Koda, Jihong Park, Mehdi Bennis, Praneeth Vepakomma, Ramesh Raskar:
AirMixML: Over-the-Air Data Mixup for Inherently Privacy-Preserving Edge Machine Learning. GLOBECOM 2021: 1-6 - [c210]Tristan Swedish, Connor Henley, Ramesh Raskar:
Objects as Cameras: Estimating High-Frequency Illumination from Shadows. ICCV 2021: 2573-2582 - [c209]Ayush Chopra, Ramesh Raskar, Jayakumar Subramanian, Balaji Krishnamurthy, Esma Senturk Gel, Santiago Romero-Brufau, Kalyan S. Pasupathy, Thomas C. Kingsley:
DeepABM: Scalable and Efficient Agent-Based Simulations Via Geometric Learning Frameworks - a Case Study For Covid-19 Spread and Interventions. WSC 2021: 1-12 - [i78]Manuel Morales, Rachel Barbar, Darshan Gandhi, Sanskruti Landage, Joseph Bae, Arpita Vats, Jil Kothari, Sheshank Shankar, Rohan Sukumaran, Himi Mathur, Krutika Misra, Aishwarya Saxena, Parth Patwa, Sethuraman T. V., Maurizio Arseni, Shailesh Advani, Kasia Jakimowicz, Sunaina Anand, Priyanshi Katiyar, Ashley Mehra, Rohan Iyer, Srinidhi Murali, Aryan Mahindra, Mikhail Dmitrienko, Saurish Srivastava, Ananya Gangavarapu, Steve Penrod, Vivek Sharma, Abhishek Singh, Ramesh Raskar:
COVID-19 Tests Gone Rogue: Privacy, Efficacy, Mismanagement and Misunderstandings. CoRR abs/2101.01693 (2021) - [i77]Rohan Iyer, Regina Rex, Kevin P. McPherson, Darshan Gandhi, Aryan Mahindra, Abhishek Singh, Ramesh Raskar:
Spatial K-anonymity: A Privacy-preserving Method for COVID-19 Related Geospatial Technologies. CoRR abs/2101.02556 (2021) - [i76]Joseph Bae, Rohan Sukumaran, Sheshank Shankar, Saurish Srivastava, Rohan Iyer, Aryan Mahindra, Qamil Mirza, Maurizio Arseni, Anshuman Sharma, Saras Agrawal, Orna Mukhopadhyay, Colin Kang, Priyanshi Katiyar, Apurv Shekhar, Sifat Hasan, Krishnendu Dasgupta, Darshan Gandhi, Sethuraman TV, Parth Patwa, Ishaan Singh, Abhishek Singh, Ramesh Raskar:
MIT SafePaths Card (MiSaCa): Augmenting Paper Based Vaccination Cards with Printed Codes. CoRR abs/2101.07931 (2021) - [i75]Rohan Sukumaran, Parth Patwa, T. V. Sethuraman, Sheshank Shankar, Rishank Kanaparti, Joseph Bae, Yash Mathur, Abhishek Singh, Ayush Chopra, Myungsun Kang, Priya Ramaswamy, Ramesh Raskar:
COVID-19 Outbreak Prediction and Analysis using Self Reported Symptoms. CoRR abs/2101.10266 (2021) - [i74]Aryan Mahindra, Chandan CV, Priyanshi Katiyar, Anshuman Sharma, Sheshank Shankar, Rohan Sukumaran, Saurish Srivastava, Armaan Bhojwani, Rohan Iyer, Ishaan Singh, Ramesh Raskar:
comparing card-based vaccine credential systems with app-based vaccine credential systems. CoRR abs/2102.04512 (2021) - [i73]Joseph Bae, Rohan Sukumaran, Sheshank Shankar, Anshuman Sharma, Ishaan Singh, Haris Nazir, Colin Kang, Saurish Srivastava, Parth Patwa, Abhishek Singh, Priyanshi Katiyar, Vitor Pamplona, Ramesh Raskar:
Mobile Apps Prioritizing Privacy, Efficiency and Equity: A Decentralized Approach to COVID-19 Vaccination Coordination. CoRR abs/2102.09372 (2021) - [i72]Praneeth Vepakomma, Julia Balla, Ramesh Raskar:
Differentially Private Supervised Manifold Learning with Applications like Private Image Retrieval. CoRR abs/2102.10802 (2021) - [i71]Abhishek Singh, Ramesh Raskar, Anna Lysyanskaya:
Safepaths: Vaccine Diary Protocol and Decentralized Vaccine Coordination System using a Privacy Preserving User Centric Experience. CoRR abs/2103.01754 (2021) - [i70]Yusuke Koda, Jihong Park, Mehdi Bennis, Praneeth Vepakomma, Ramesh Raskar:
AirMixML: Over-the-Air Data Mixup for Inherently Privacy-Preserving Edge Machine Learning. CoRR abs/2105.00395 (2021) - [i69]Parth Patwa, Viswanatha Reddy, Rohan Sukumaran, Sethuraman TV, Eptehal Nashnoush, Sheshank Shankar, Rishemjit Kaur, Abhishek Singh, Ramesh Raskar:
Can Self Reported Symptoms Predict Daily COVID-19 Cases? CoRR abs/2105.08321 (2021) - [i68]Subhash Chandra Sadhu, Abhishek Singh, Tomohiro Maeda, Tristan Swedish, Ryan Kim, Lagnojita Sinha, Ramesh Raskar:
Automatic calibration of time of flight based non-line-of-sight reconstruction. CoRR abs/2105.10603 (2021) - [i67]Praneeth Vepakomma, Yulia Kempner, Ramesh Raskar:
Parallel Quasi-concave set optimization: A new frontier that scales without needing submodularity. CoRR abs/2108.08758 (2021) - [i66]Ayush Chopra, Esma Senturk Gel, Jayakumar Subramanian, Balaji Krishnamurthy, Santiago Romero-Brufau, Kalyan S. Pasupathy, Thomas C. Kingsley, Ramesh Raskar:
DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks. CoRR abs/2110.04421 (2021) - [i65]Praneeth Vepakomma, Subha Nawer Pushpita, Ramesh Raskar:
Private measurement of nonlinear correlations between data hosted across multiple parties. CoRR abs/2110.09670 (2021) - [i64]Ayush Chopra, Surya Kant Sahu, Abhishek Singh, Abhinav Java, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar:
AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learning. CoRR abs/2112.01637 (2021) - [i63]Shraman Pal, Mansi Uniyal, Jihong Park, Praneeth Vepakomma, Ramesh Raskar, Mehdi Bennis, Moongu Jeon, Jinho Choi:
Server-Side Local Gradient Averaging and Learning Rate Acceleration for Scalable Split Learning. CoRR abs/2112.05929 (2021) - 2020
- [j89]Ramesh Raskar, Deepti Pahwa, Robson Beaudry:
Contact Tracing: Holistic Solution Beyond Bluetooth. IEEE Data Eng. Bull. 43(2): 67-70 (2020) - [c208]Agastya Kalra, Vage Taamazyan, Supreeth Krishna Rao, Kartik Venkataraman, Ramesh Raskar, Achuta Kadambi:
Deep Polarization Cues for Transparent Object Segmentation. CVPR 2020: 8599-8608 - [c207]Connor Henley, Tomohiro Maeda, Tristan Swedish, Ramesh Raskar:
Imaging Behind Occluders Using Two-Bounce Light. ECCV (29) 2020: 573-588 - [c206]Praneeth Vepakomma, Abhishek Singh, Otkrist Gupta, Ramesh Raskar:
NoPeek: Information leakage reduction to share activations in distributed deep learning. ICDM (Workshops) 2020: 933-942 - [c205]Jack Erdozain, Kazuto Ichimaru, Tomohiro Maeda, Hiroshi Kawasaki, Ramesh Raskar, Achuta Kadambi:
3d Imaging For Thermal Cameras Using Structured Light. ICIP 2020: 2795-2799 - [c204]David B. Lindell, Matthew O'Toole, Srinivasa G. Narasimhan, Ramesh Raskar:
Computational time-resolved imaging, single-photon sensing, and non-line-of-sight imaging. SIGGRAPH Courses 2020: 5:1-5:119 - [c203]Ramesh Raskar, Andreas Velten, Sebastian Bauer, Tristan Swedish:
Seeing around corners using time of flight. SIGGRAPH Courses 2020: 12:1-12:97 - [i62]Ramesh Raskar, Isabel Schunemann, Rachel Barbar, Kristen Vilcans, Jim Gray, Praneeth Vepakomma, Suraj Kapa, Andrea Nuzzo, Rajiv Gupta, Alex Berke, Dazza Greenwood, Christian Keegan, Shriank Kanaparti, Robson Beaudry, David Stansbury, Beatriz Botero Arcila, Rishank Kanaparti, Vitor F. Pamplona, Francesco M. Benedetti, Alina Clough, Riddhiman Das, Kaushal Jain, Khahlil Louisy, Greg Nadeau, Vitor Pamplona, Steve Penrod, Yasaman Rajaee, Abhishek Singh, Greg Storm, John Werner:
Apps Gone Rogue: Maintaining Personal Privacy in an Epidemic. CoRR abs/2003.08567 (2020) - [i61]Alex Berke, Michiel A. Bakker, Praneeth Vepakomma, Ramesh Raskar, Kent Larson, Alex 'Sandy' Pentland:
Assessing Disease Exposure Risk With Location Histories And Protecting Privacy: A Cryptographic Approach In Response To A Global Pandemic. CoRR abs/2003.14412 (2020) - [i60]Fatemehsadat Mireshghallah, Mohammadkazem Taram, Praneeth Vepakomma, Abhishek Singh, Ramesh Raskar, Hadi Esmaeilzadeh:
Privacy in Deep Learning: A Survey. CoRR abs/2004.12254 (2020) - [i59]Manish Shukla, Rajan M. A, Sachin Lodha, Gautam Shroff, Ramesh Raskar:
Privacy Guidelines for Contact Tracing Applications. CoRR abs/2004.13328 (2020) - [i58]Tomohiro Maeda, Ankit Ranjan, Ramesh Raskar:
Automatic Differentiation for All Photons Imaging to See Inside Volumetric Scattering Media. CoRR abs/2006.01897 (2020) - [i57]Ramesh Raskar, Greg Nadeau, John Werner, Rachel Barbar, Ashley Mehra, Gabriel Harp, Markus Leopoldseder, Bryan Wilson, Derrick Flakoll, Praneeth Vepakomma, Deepti Pahwa, Robson Beaudry, Emelin Flores, Maciej Popielarz, Akanksha Bhatia, Andrea Nuzzo, Matt Gee, Jay Summet, Rajeev Surati, Bikram Khastgir, Francesco Maria Benedetti, Kristen Vilcans, Sienna Leis, Khahlil Louisy:
COVID-19 Contact-Tracing Mobile Apps: Evaluation and Assessment for Decision Makers. CoRR abs/2006.05812 (2020) - [i56]Ramesh Raskar, Abhishek Singh, Sam Zimmerman, Shrikant Kanaparti:
Adding Location and Global Context to the Google/Apple Exposure Notification Bluetooth API. CoRR abs/2007.02317 (2020) - [i55]Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram, Salman Avestimehr:
FedML: A Research Library and Benchmark for Federated Machine Learning. CoRR abs/2007.13518 (2020) - [i54]Iker Ceballos, Vivek Sharma, Eduardo Mugica, Abhishek Singh, Alberto Roman, Praneeth Vepakomma, Ramesh Raskar:
SplitNN-driven Vertical Partitioning. CoRR abs/2008.04137 (2020) - [i53]Priyanka Singh, Abhishek Singh, Gabriel Cojocaru, Praneeth Vepakomma, Ramesh Raskar:
PPContactTracing: A Privacy-Preserving Contact Tracing Protocol for COVID-19 Pandemic. CoRR abs/2008.06648 (2020) - [i52]Ramesh Raskar, Ranu Dhillon, Suraj Kapa, Deepti Pahwa, Renaud Falgas, Lagnojita Sinha, Aarathi Prasad, Abhishek Singh, Andrea Nuzzo, Rohan Iyer, Vivek Sharma:
Comparing manual contact tracing and digital contact advice. CoRR abs/2008.07325 (2020) - [i51]Praneeth Vepakomma, Abhishek Singh, Otkrist Gupta, Ramesh Raskar:
NoPeek: Information leakage reduction to share activations in distributed deep learning. CoRR abs/2008.09161 (2020) - [i50]Sheshank Shankar, Ayush Chopra, Rishank Kanaparti, Myungsun Kang, Abhishek Singh, Ramesh Raskar:
Proximity Sensing for Contact Tracing. CoRR abs/2009.04991 (2020) - [i49]Ramesh Raskar, Sai Sri Sathya:
Bluetooth based Proximity, Multi-hop Analysis and Bi-directional Trust: Epidemics and More. CoRR abs/2009.06468 (2020) - [i48]Mikhail Dmitrienko, Abhishek Singh, Patrick Erichsen, Ramesh Raskar:
Proximity Inference with Wifi-Colocation during the COVID-19 Pandemic. CoRR abs/2009.12699 (2020) - [i47]Ananya Gangavarapu, Ellie Daw, Abhishek Singh, Rohan Iyer, Gabriel Harp, Sam Zimmerman, Ramesh Raskar:
Target Privacy Threat Modeling for COVID-19 Exposure Notification Systems. CoRR abs/2009.13300 (2020) - [i46]Darshan Gandhi, Rohan Sukumaran, Priyanshi Katiyar, Alex Radunsky, Sunaina Anand, Shailesh Advani, Jil Kothari, Kasia Jakimowicz, Sheshank Shankar, Sethuraman T. V., Krutika Misra, Aishwarya Saxena, Sanskruti Landage, Richa Sonker, Parth Patwa, Aryan Mahindra, Mikhail Dmitrienko, Kanishka Vaish, Ashley Mehra, Srinidhi Murali, Rohan Iyer, Joseph Bae, Vivek Sharma, Abhishek Singh, Rachel Barbar, Ramesh Raskar:
Digital Landscape of COVID-19 Testing: Challenges and Opportunities. CoRR abs/2012.01772 (2020) - [i45]